Digital multifunction reprographic systems are now well known and have replaced optical reprographic systems as a way to reproduce images. In these conventional digital multifunction reprographic systems, a scanner accepts a document to be copied and converts the document into electronic image(s). These images, usually in the form of pages, are then passed to a central control unit which may re-order or reorganize these pages and then, depending on the request of the user of the device, send the pages or images to a destination. Often this destination is an attached printing unit which makes one or more copies of the original document.
However, these conventional devices perform many other functions besides simple copying. The central control unit is usually equipped with a combination of hardware and software elements that enable it to accept input from other sources. The other sources may include some sort of network interface and/or an interface to a telephone system to enable FAX input.
The network interface is usually configured so that it can accept jobs to be printed from any computer source that is connected to the network. This configuration normally includes elements that can convert input documents formatted in one or more page description languages (PDLs) to the native format of the printing device.
An important inner component of such a conventional multifunction digital device is the image path. This is the combination of software and hardware elements that accepts the electronic images from the multiplicity of sources and performs any operations needed to convert the images to the format desired for the various output paths. The image path is usually one of the more complex and costly components of such digital multifunction devices.
The image path for a conventional multifunction device usually has several constraints. One the hand, there is a desire to make the image path utilize data in a multi-bit per pixel format so as to provide for maximum image quality and a minimum loss of critical information in the transformation of documents from paper to electronic form. On the other hand, there are cost constraints and perhaps performance limits on the devices or software that comprise the image path.
Conventional image path electronics may also utilize binary image paths. In this situation, if the input information is scanned in a binary manner at sufficiently high resolution, the scanned image can be reconstructed at the output with little or no perceptible loss of image quality.
Another component of many conventional multifunction devices, especially for those devices having a printing engine that is capable of producing colored output, is the use of analog modulation schemes for the output. In these devices, analog data, in the form of multi-bit pixels, is presented to the modulator of the output printing device. The modulator compares the analog equivalent of the input byte of data to a periodic saw tooth wave. The output therefrom is a signal to the laser imaging component that is pulsewidth modulated by the data stream.
One way to implement the resolution coverage is to pass the binary data through a digital equivalent of a two-dimensional low pass filter. The digital equivalent of a two-dimensional low pass filter may replace each pixel in the binary image by the average of the values within some window centered on the pixel of interest. While such a system does an adequate job of converting the high resolution binary data to analog data, these solutions also have the deleterious effect of smearing sharp edges in the original document. Such an effect is particularly detrimental when reproducing text and line art.
FIG. 1 shows, in schematic form, an example of a conventional filtering process. For this illustrative example, a 3×3 pixel filter is described. It is noted that any size filter may be utilized. Moreover, the pixel filter may perform simple averaging or be constructed of a more complex filter kernel. Notwithstanding the size or complexity of the filter, a description of a simple 3×3 pixel filter example will provide a demonstration of the principles of operation of this filter.
In FIG. 1, a portion of an image 101, in the form of a matrix, is shown. In the portion of the image 101, a vertical edge transitioning from black to white is shown, whereby a black region, represented by the numeric binary values “1” and slashed boxes, occupies the leftmost vertical column, and a white region, represented by the numeric binary values “0” and non-slashed boxes, occupies the center and rightmost vertical columns of the portion of the image 101. A filter kernel 102 provide a simple matrix of filter weights wherein an output pixel is the evenly weighted average of the nine pixels covered by the filter kernel 102. After a filter 104 performs the filtering operation, a portion of a output image 103 is generated.
The portion of the output image 103, as illustrated in FIG. 1, demonstrates that the original sharp edge of the portion of the image 101 has been smeared. More specifically, the original edge of the portion of the image 101 made the transition from “1” to “0” in a width of a single pixel. On the other hand, the filtered edge of the portion of the output image 103 now covers a width of three pixels.
In other words, when the pixel A of the portion of the image 101 of FIG. 1 is processed by the filter 104, the output pixel A′ of the portion of the output image 103 has a value of zero indicating, in this example, a white region, assuming that the column to the right of the rightmost illustrated column contained only “0” values. It is noted that the pixel of interest has a filter position that is associated with the highlighted pixel position F. Moreover, when the pixel B of the portion of the image 101 is processed by the filter 104, the output pixel B′ of the portion of the output image 103 has a value of “⅓” indicating, in this example, a grey region. Furthermore, when the pixel C of the portion of the image 101 is processed by the filter 104, the output pixel C′ of the portion of the output image 103 has a value of “⅔” indicating, in this example, a grey region. Lastly, as illustrated, when the two columns to the left of the leftmost illustrated column contain only “1” values and the center pixel D of the portion of the image 101 is processed by the filter 104, the resulting output pixel D′ of the portion of the output image 103 has a value of “1” indicating, in this example, a black region.
FIG. 2 shows a block diagram of a conventional device to implement the process illustrated in FIG. 1 and described above. As illustrated in FIG. 2, image data 201 is sent to a digital filter module 202, which accepts the image data and filter kernel data 203 and digitally filters to the image data. The output of digital filter module 202 is sent to an image output terminal (IOT) 250, which converts the image data to a hard copy of the image.
As noted above, the blurring of the output edge can be resolved through the use of tag data in conjunction with the image data. More specifically, if the pixel in question within the binary image is matched with a tag bit that indicates that it is an edge pixel, the filter is not applied to that pixel, but an analog level corresponding to high or low density, as the binary image bit is one or zero is output instead. FIG. 3 provides an illustration of this tag data integrated process.
In FIG. 3, a portion of an image 301, in the form of a matrix, is shown. In the portion of the image 301, a vertical edge transitioning from black to white is shown, whereby a black region, represented by the numeric binary values “1” and slashed boxes, occupies the leftmost vertical column, and a white region, represented by the numeric binary values “0” and non-slashed boxes, occupies the center and rightmost vertical columns of the portion of the image 301. A filter kernel 302 provides a simple matrix of filter weights wherein an output pixel is the evenly weighted average of the nine pixels covered by the filter kernel 302. After a filter 304 performs the filtering operation, a portion of a output image 303 is generated.
The portion of the output image 303, as illustrated in FIG. 3, demonstrates that the original sharp edge of the portion of the image 301 has been converted to a sharp edge 306 with a ghost image artifact 307. More specifically, the original edge of the portion of the image 301 made the transition from “1” to “0” in a width of a single pixel. On the other hand, the filtered edge 306 of the portion of the output image 303 has a transition 306 from “1” to “0” being a width of a single pixel and a ghost artifact 307.
In other words, when the pixel A of the portion of the image 301 of FIG. 3 is processed by the filter 304, the output pixel A′ of the portion of the output image 303 has a value of “¼” indicating, in this example, a ghost artifact 307, assuming that the column to the right of the rightmost illustrated column contained only “0” values. It is noted that the pixel of interest has a filter position that is associated with the highlighted pixel position F. Since pixel A of the portion of the image 301 had not been tagged as an edge, the filter value for the pixel A of the portion of the image 301 is selected as the output value for output pixel A′ of the portion of the output image 303. This selection of the filter value means that the output value includes the residual filter values, thereby creating the ghost artifact 307.
Moreover, when the pixel B of the portion of the image 301 is processed by the filter 304, the output pixel B′ of the portion of the output image 303 has a value of “0” indicating, in this example, a white region because pixel B of the portion of the image 301 had been tagged as an edge, and thus, the filter value for the pixel B of the portion of the image 301 is not selected as the output value for output pixel B′ of the portion of the output image 303, but the actual value of pixel B of the portion of the image 301 is passed through as the output pixel B′ of the portion of the output image 303.
Furthermore, when the pixel C of the portion of the image 301 is processed by the filter 304, the output pixel C′ of the portion of the output image 303 has a value of “1” indicating, in this example, a black region because pixel C of the portion of the image 301 had been tagged as an edge, and thus, the filter value for the pixel C of the portion of the image 301 is not selected as the output value for output pixel C′ of the portion of the output image 303, but the actual value of pixel C of the portion of the image 301 is passed through as the output pixel C′ of the portion of the output image 303.
Lastly, when the two columns to the left of the leftmost illustrated column contain only “1” values and the center pixel D of the portion of the image 301 is processed by the filter 304, the resulting output pixel D′ of the portion of the output image 303 has a value of “1” indicating, in this example, a black region because pixel D of the portion of the image 301 had not been tagged as an edge, and thus, the filter value for the pixel D of the portion of the image 301 is selected as the output value for output pixel D′ of the portion of the output image 303.
FIG. 4 shows a block diagram of another conventional device to implement the process illustrated in FIG. 3 and described above. As illustrated in FIG. 4, image data 401 is sent to two modules. The first module, a digital filter module 402, accepts the image data and filter kernel data 403 and digitally filters the image data. The second module, a “255/0” module 404, outputs either 255 (all 8 bits ON) or 0 (all 8 bits OFF) depending on whether the input pixel has a value of “1” or “0.” The output of these two modules is sent to a selector module 405. The output of the selector module 405, which is controlled by the tag data stream 406, is sent to an image output terminal (IOT) 450, which converts the image data to a hard copy of the image. If the tag bit is 1, the selector output is identical to the “255/0” module 404, and if the tag bit is 0, the selector output is identical to the output of the digital filter module 402.
However, as demonstrated above, the conventional edge reconstruction process can generate artifacts that while less objectionable than the softening of a simple filtering process are nevertheless detrimental to the overall quality of the resulting image. FIG. 7 shows an example of how the conventional edge reconstruction process can create an artifact, ghost image 710. As described above, an image is processed to create the desired image 700, but due to the filtering process, an artifact, a ghost image 710, is also created. The artifact, a ghost image 710, arises because the edge pixels are included in the filtering process.
As discussed above, a variety of conventional systems have addressed this issue by attempting to minimize the edge softening of the filter. Another such system, as described in U.S. Pat. No. 6,130,966, adds a second bit to each pixel, where the second bit “tags” the pixel wherein the tag indicates whether or not the pixel is part of an edge. This tag information is carried through the image path and can be used in other places besides the output conversion stage to modify processing of the image data to best preserve edge information and sharpness. The entire content of U.S. Pat. No. 6,130,966 is hereby incorporated by reference.
Although some conventional systems have attempted to minimize the edge softening of the filter, artifacts can still be created near edges in the analog output. These artifacts detract from the perceived quality of the output.
Therefore, it is desirable to provide a system or methodology that implements a conversion of high resolution binary image data to analog that prevents the smearing of sharp edges and is substantially free of edge artifacts.
One aspect of a method that converts edge-tagged pixels of image data to pixels of contone image data determines a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; filters, using a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, each image value of each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; assigns, a predetermined filtered image value to each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel; sums all filtered image values for the predefined neighborhood of pixels to produce an image data sum value; and assigns, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, the image data sum value as an image data value for the first pixel of contone image data.
Another aspect of a method that extends edge-tagged pixels of image data to pixels of contone image data determines a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; determines a number, N, pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to 1/N and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0; filters, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels; sums all filtered image values for the predefined neighborhood of pixels to produce an image data sum value; and assigns the image data sum value as an image data value for the first pixel of contone image data.
A further aspect of a method that extends edge-tagged pixels of image data to pixels of contone image data determines a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; determines a sum, S, of all filter weighting values within the predetermined set of filter weighting values associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to a product of the predetermined filter weighting value and 1/S and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0; filters, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels; sums all filtered image values for the predefined neighborhood of pixels to produce an image data sum value; and assigns the image data sum value as an image data value for the first pixel of contone image data.
Another aspect of a method that extends edge-tagged pixels of image data to pixels of contone image data determines a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; determines a number, N, pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to 1/N and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0; sums, only filter weighting values that are associated with pixels within the predefined neighborhood of pixels having an image value indicating a non-zero intensity value, to produce an image data sum value; and assigns the image data sum value as an image data value for the first pixel of contone image data.
Another aspect of a method that extends edge-tagged pixels of image data to pixels of contone image data determines a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; determines a sum, S, of all filter weighting values within the predetermined set of filter weighting values associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to a product of the predetermined filter weighting value and 1/S and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0; modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0; sums, only filter weighting values that are associated with pixels within the predefined neighborhood of pixels having an image value indicating a non-zero intensity value, to produce an image data sum value; and assigns the image data sum value as an image data value for the first pixel of contone image data.
One aspect of a system that converts edge-tagged pixels of image data to pixels of contone image data includes a selection circuit to determine a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data; a filter circuit to filter, using a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, each image value of each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel; and an accumulator to sum all filtered image values for the predefined neighborhood of pixels to produce an image data sum value. The selection circuit selects a predetermined filtered image value for each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel. The selection circuit selects the filtered image value from the filter circuit for each pixel of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel.
Another aspect of a system that extends edge-tagged pixels of image data to pixels of contone image data includes a filter weight modifier circuit to determine a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data. The filter weight modifier circuit determines a number, N, pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to 1/N and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0. The system also includes a filter circuit to filter, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels, to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels and to sum all filtered image values for the predefined neighborhood of pixels to produce an image data sum value an image data value for the first pixel of contone image data.
Another aspect of a system that extends edge-tagged pixels of image data to pixels of contone image data includes a filter weight modifier circuit to determine a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data. The filter weight modifier circuit determines a sum, S, of all filter weighting values within the predetermined set of filter weighting values associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to a product of the predetermined filter weighting value and 1/S and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0. The system also includes a filter circuit to filter, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels, to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels and to sum all filtered image values for the predefined neighborhood of pixels to produce an image data sum value as an image data value for the first pixel of contone image data.
Another aspect of a system that extends edge-tagged pixels of image data to pixels of contone image data includes a filter weight modifier circuit to determine a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data. The filter weight modifier circuit determines a number, N, pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to 1/N and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0. The system also includes a filter circuit to filter, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels, to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels and to sum, only filter weighting values that are associated with pixels within the predefined neighborhood of pixels having an image value indicating a non-zero intensity value, to produce an image data sum value as an image data value for the first pixel of contone image data.
Another aspect of a system that extends edge-tagged pixels of image data to pixels of contone image data includes a filter weight modifier circuit to determine a tagged state value of each pixel of image data within a predefined neighborhood of pixels, each pixel of image data within the predefined neighborhood of pixels having an associated image value, a first pixel of image data within the predefined neighborhood of pixels being associated a first pixel of contone image data. The filter weight modifier circuit determines a sum, S, of all filter weighting values within the predetermined set of filter weighting values associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is a non-edge pixel, a predetermined set of filter weighting values wherein each pixel of image data within the predefined neighborhood of pixels has an associated filter weighting value, such that each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is a non-edge pixel is equal to a product of the predetermined filter weighting value and 1/S and each filter weighting value associated with pixels of image data within the predefined neighborhood of pixels having a tagged state value indicating that the pixel of image data is an edge pixel is equal to 0. The filter weight modifier circuit modifies, when the tagged state value of the first pixel of image data indicates the first pixel of image data is an edge pixel, the predetermined set of filter weighting values such that the filter weighting value associated with the first pixel of image data is equal to 1 and each filter weighting value associated with a non-first pixel of image data within the predefined neighborhood of pixels is equal to 0. The system also includes a filter circuit to filter, using the modified set of filter weighting values, each pixel of image data within the predefined neighborhood of pixels, to generate a filtered image value for each pixel of image data within the predefined neighborhood of pixels and to sum, only filter weighting values that are associated with pixels within the predefined neighborhood of pixels having an image value indicating a non-zero intensity value, to produce an image data sum value as an image data value for the first pixel of contone image data.